Doubly robust imputation procedures for finite population means in the presence of a large number of zeros

DOI10.1002/cjs.11230zbMath1330.62063OpenAlexW2164246043MaRDI QIDQ5175769

Christian-Olivier Nambeu, David Haziza, Guillaume Chauvet

Publication date: 25 February 2015

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/cjs.11230

zbMATH Keywords

variance estimationitem nonresponsedeterministic imputationrandom imputationbalanced imputation

Mathematics Subject Classification ID

Sampling theory, sample surveys (62D05) Nonparametric statistical resampling methods (62G09)

Related Items (6)

Robust quasi‐randomization‐based estimation with ensemble learning for missing data ⋮ Multiply robust imputation procedures for zero-inflated distributions in surveys ⋮ Recent Developments in Dealing with Item Non‐response in Surveys: A Critical Review ⋮ Exact balanced random imputation for sample survey data ⋮ Preserving the distribution function in surveys in case of imputation for zero inflated data ⋮ Doubly Robust Inference for the Distribution Function in the Presence of Missing Survey Data

Cites Work

• Unnamed Item
• Doubly robust point and variance estimation in the presence of imputed survey data
• On balanced random imputation in surveys
• Efficient balanced sampling: The cube method
• Fully efficient estimation of coefficients of correlation in the presence of imputed survey data
• Fractional hot deck imputation
• Jackknife variance estimation with survey data under hot deck imputation
• Inference and missing data
• Empirical likelihood confidence intervals for the mean of a population containing many zero values
• Variance Estimation for Survey Data with Composite Imputation and Nonnegligible Sampling Fractions
• Survey Design Under the Regression Superpopulation Model

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